Graph Image Privacy (GIP) [1]} replaces the social relationship nodes with two nodes representing the privacy classes (private, public) for the image privacy classification task.
The Dynamic Region-Aware Graph Convolutional Network (DRAG) [2]} adaptively models the correlation between important regions of the image (including objects) using a self-attention mechanism. DRAG [2]} consists of a Graph Convolutional Network (GCN) [4]} that learns the relationships among specific regions in the image without the use of object recognition.
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